Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures

Joongheon Kim, Wonjun Lee, Dongshin Kim, Eunkyo Kim, Hyeokman Kim, Sanghyun Ahn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper proposes dynamic clustering for coverage-time maximization (DC-CTM) in sensor networks. The coverage-time is defined as the time until one of cluster heads (CHs) runs out of energy in clustering-based sensor networks. DC-CTM regulates cluster radii for balanced energy consumption among CHs for coverage-time maximization. By using DC-CTM, three advantages can be achieved. The first one is balanced energy consumption among CHs. The second one is minimized energy consumption in each CH. The last one is the consideration of mobility on CHs. The novelty of proposed scheme, DC-CTM scheme, is shown by various simulation-based performance analyses.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages652-661
Number of pages10
Volume4096 LNCS
Publication statusPublished - 2006 Aug 9
EventInternational Conference on Embedded and Ubiquitous Computing, EUC 2006 - Seoul, Korea, Republic of
Duration: 2006 Aug 12006 Aug 4

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4096 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

OtherInternational Conference on Embedded and Ubiquitous Computing, EUC 2006
CountryKorea, Republic of
CitySeoul
Period06/8/106/8/4

Fingerprint

Hierarchical Networks
Network Architecture
Network architecture
Sensor networks
Sensor Networks
Cluster Analysis
Coverage
Clustering
Head
Energy utilization
Energy Consumption
Radius
Energy

ASJC Scopus subject areas

  • Computer Science(all)
  • Biochemistry, Genetics and Molecular Biology(all)
  • Theoretical Computer Science

Cite this

Kim, J., Lee, W., Kim, D., Kim, E., Kim, H., & Ahn, S. (2006). Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4096 LNCS, pp. 652-661). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4096 LNCS).

Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures. / Kim, Joongheon; Lee, Wonjun; Kim, Dongshin; Kim, Eunkyo; Kim, Hyeokman; Ahn, Sanghyun.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4096 LNCS 2006. p. 652-661 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4096 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kim, J, Lee, W, Kim, D, Kim, E, Kim, H & Ahn, S 2006, Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 4096 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4096 LNCS, pp. 652-661, International Conference on Embedded and Ubiquitous Computing, EUC 2006, Seoul, Korea, Republic of, 06/8/1.
Kim J, Lee W, Kim D, Kim E, Kim H, Ahn S. Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4096 LNCS. 2006. p. 652-661. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
Kim, Joongheon ; Lee, Wonjun ; Kim, Dongshin ; Kim, Eunkyo ; Kim, Hyeokman ; Ahn, Sanghyun. / Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4096 LNCS 2006. pp. 652-661 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
@inproceedings{afa2834d657047578d596b000139da12,
title = "Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures",
abstract = "This paper proposes dynamic clustering for coverage-time maximization (DC-CTM) in sensor networks. The coverage-time is defined as the time until one of cluster heads (CHs) runs out of energy in clustering-based sensor networks. DC-CTM regulates cluster radii for balanced energy consumption among CHs for coverage-time maximization. By using DC-CTM, three advantages can be achieved. The first one is balanced energy consumption among CHs. The second one is minimized energy consumption in each CH. The last one is the consideration of mobility on CHs. The novelty of proposed scheme, DC-CTM scheme, is shown by various simulation-based performance analyses.",
author = "Joongheon Kim and Wonjun Lee and Dongshin Kim and Eunkyo Kim and Hyeokman Kim and Sanghyun Ahn",
year = "2006",
month = "8",
day = "9",
language = "English",
isbn = "3540366792",
volume = "4096 LNCS",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
pages = "652--661",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

}

TY - GEN

T1 - Dynamic clustering for coverage-time maximization in two-tiered hierarchical sensor network architectures

AU - Kim, Joongheon

AU - Lee, Wonjun

AU - Kim, Dongshin

AU - Kim, Eunkyo

AU - Kim, Hyeokman

AU - Ahn, Sanghyun

PY - 2006/8/9

Y1 - 2006/8/9

N2 - This paper proposes dynamic clustering for coverage-time maximization (DC-CTM) in sensor networks. The coverage-time is defined as the time until one of cluster heads (CHs) runs out of energy in clustering-based sensor networks. DC-CTM regulates cluster radii for balanced energy consumption among CHs for coverage-time maximization. By using DC-CTM, three advantages can be achieved. The first one is balanced energy consumption among CHs. The second one is minimized energy consumption in each CH. The last one is the consideration of mobility on CHs. The novelty of proposed scheme, DC-CTM scheme, is shown by various simulation-based performance analyses.

AB - This paper proposes dynamic clustering for coverage-time maximization (DC-CTM) in sensor networks. The coverage-time is defined as the time until one of cluster heads (CHs) runs out of energy in clustering-based sensor networks. DC-CTM regulates cluster radii for balanced energy consumption among CHs for coverage-time maximization. By using DC-CTM, three advantages can be achieved. The first one is balanced energy consumption among CHs. The second one is minimized energy consumption in each CH. The last one is the consideration of mobility on CHs. The novelty of proposed scheme, DC-CTM scheme, is shown by various simulation-based performance analyses.

UR - http://www.scopus.com/inward/record.url?scp=33746715118&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=33746715118&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:33746715118

SN - 3540366792

SN - 9783540366799

VL - 4096 LNCS

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 652

EP - 661

BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -